六氟化硫气体取样分析及尾气回收处理系统研究

Research on SF_(6)Gas Sampling and Analysis and Tail Gas Recovery and Treatment System

针对六氟化硫(SF_(6))气体取样分析及尾气回收处理过程中,SF_(6)气体存在严重泄漏的问题,设计了一种基于差分光声光谱法的气体检测方法。该方法通过利用分子红外吸收光谱技术,实现了万亿分比浓度或十亿分比浓度量级的气体检测功能,避免了空气自身光声效应的干扰。通过构建设备状态空间模型,基于粒子滤波算法对卡尔曼滤波法进行扩展,比较状态变量实时测量值与状态估计值得到的残差值。对气体泄漏进行预警,同时加入自适应阈值方法检测设备故障,以避免模型误差以及噪声的干扰造成误报警。试验结果显示,当检测到电流为1000 A时,振动信号为0.89 V。所提系统对触头气体泄漏和放点故障的预警效果较好。

Aiming at the problem of serious leakage of SF_(6) gas during sampling and analysis of SF_(6) gas and tail gas recovery and treatment,a gas detection method based on differential photoacoustic spectrometry is designed.The method realizes the gas detection function in the order of trillion-decibel concentration or billion-decibel concentration by utilizing the molecular infrared absorption spectroscopy technology and avoids the interference of the photoacoustic effect of the air itself.By constructing a state space model of the equipment and extending the Kalman filtering method based on the particle filter algorithm,the residual values obtained by comparing the real-time measured values of the state variables with the estimated values of the state.Early warning is provided for gas leakage,and at the same time an adaptive threshold method is added to detect equipment faults to avoid false alarms caused by modeling errors as well as the interference of noise.The experimental results show that the vibration signal is 0.89 V when the current is detected as 1000 A.The proposed system is effective in early warning of contact gas leakage and release point faults.